This research builds from existing scholarship to highlight the important role social complexity plays on managing and mitigating wildfire risk in the wildland-urban interface.
In 2023, all regions of British Columbia (BC) experienced record-breaking fire weather and wildfires, with extreme behavior and social-ecological effects. In total, 2245 wildfires burned 2840 545 hectares. Contemporary wildfires are the culmination of a century of altered human–forest–wildfire relationships, exacerbated by climate change.
Wildfires are having disproportionate impacts on U.S. households. Notably, in California, over half of wildfire-destroyed homes (54%) are in low-income areas. We investigate the relationship between social vulnerability and wildfire community preparedness using building permits from 16 counties in California with 2.9 million buildings (2013–2021) and the U.S.
Researchers have sought to understand why wildland urban interface areas continue to expand in the United States despite increasing riskand loss to those areas.
Destructive wildfire disasters are escalating globally, challenging existing fire management paradigms. The establishment of defensible space around homes in wildland and rural urban interfaces can help to reduce the risk of house loss and provide a safe area for residents and firefighters to defend the property from wildfire.
Wildfire is increasing in frequency, extent, and severity in many parts of the USA. Considering the unequal burden of natural hazards on socially vulnerable populations, we ask here, how are characteristics of social vulnerability associated with wildfire occurrence nationwide, at different scales and across differing levels of wildland–urban interface development?
Wildfire risk is increasing all over the world, particularly in the western United States and the communities in wildland-urban interface (WUI) areas are at the greatest risk of fire.
Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown.
As wildfires increase in both severity and frequency, understanding the role of risk saliency on human behaviors in the face of fire risks becomes paramount. While research has shown that homebuyers capitalize wildfire risk following a fire, studies of the role that risk saliency plays on residential development is limited.